Simulating Smoking Behaviors Based on Cognition-Determined Communication of Opinions
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Cyber attacks pose a major threat to modern organizations. Little is known about the social aspects of decision making among organizations that face cyber threats, nor do we have empirically-grounded models of the dynamics of cooperative behavior among vulnerable organizations. The effectiveness of cyber defense can likely be enhanced if information and resources are shared among organizations that face similar threats. Three models were created to begin to understand the cognitive and social aspects of cyber cooperation. The first simulated a cooperative cyber security program between two organizations. The second focused on a cyber security training program in which participants interact (and potentially cooperate) to solve problems. The third built upon the first two models and simulates cooperation between organizations in an information-sharing program.
As the US continues its vigilance against distributed, embedded threats, understanding the political and social structure of these groups becomes paramount for predicting and dis- rupting their attacks. Agent-based models (ABMs) serve as a powerful tool to study these groups. While the popularity of social network tools (e.g., Facebook, Twitter) has provided extensive communication data, there is a lack of ne-grained behavioral data with which to inform and validate existing ABMs. Virtual worlds, in particular massively multiplayer online games (MMOG), where large numbers of people interact within a complex environ- ment for long periods of time provide an alternative source of data. These environments provide a rich social environment where players engage in a variety of activities observed between real-world groups: collaborating and/or competing with other groups, conducting battles for scarce resources, and trading in a market economy. Strategies employed by player groups surprisingly re ect those seen in present-day con icts, where players use diplomacy or espionage as their means for accomplishing their goals. In this project, we propose to address the need for ne-grained behavioral data by acquiring and analyzing game data a commercial MMOG, referred to within this report as Game X. The goals of this research were: (1) devising toolsets for analyzing virtual world data to better inform the rules that govern a social ABM and (2) exploring how virtual worlds could serve as a source of data to validate ABMs established for analogous real-world phenomena. During this research, we studied certain patterns of group behavior to compliment social modeling e orts where a signi cant lack of detailed examples of observed phenomena exists. This report outlines our work examining group behaviors that underly what we have termed the Expression-To-Action (E2A) problem: determining the changes in social contact that lead individuals/groups to engage in a particular behavior. Results from our work indicate that virtual worlds have the potential for serving as a proxy in allocating and populating behaviors that would be used within further agent-based modeling studies.
System Dynamics Review
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Proposed for publication in Reliability Engineering and System Safety.
Abstract not provided.
Proposed for publication in Reliability Engineering and System Safety.
Abstract not provided.
Proposed for publication in Reliability Engineering and System Safety.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Abstract not provided.